Sensors, such as analog sensors, are widely used in various applications, such as smartphones, tablet computers, laptops, Internet of Things (IoT), and other portable or wearable devices. Some of the sensors may be used to monitor device-related or human body-related events like physical activity, gestures, speech, health, emotional state, etc. The performance of these sensors, in particular, signals obtained from them, may depend on their sensitivity toward electromagnetic interference (EMI). In some instances, such as for IoT devices or biosensing devices, the sensed signals provided by the sensors, as a result, the data provided, may be distorted or corrupted by EMI. The signal corruption may occur because many sensors, in particular, analog sensors, may be prone to interference (signal to interference ratio) of 0 dB to −10 db or beyond for the in-band frequency range, and also for the out-of-band frequency range noise. For example, an audio sensor may operate at a signal amplitude of 1 mV to 10 mV for a frequency range from 20 Hz to 20 KHz. In another example, medical implanted devices may operate in the frequency range of 1 KHz to 10 MHz and signal amplitude in the range of 10 uV to 10 mV. Filtering interference in these frequency bands may require higher order filtering, which may result in increased bill of materials (BOM) cost.